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Previous work has benchmarked multiple speech recognition systems in terms of Word Error Rate (WER) for speech intended for artificial agents. This metric allows us to compare recognizers in terms of the frequency of errors, however errors are not equally meaningful in terms of their impact on understanding the utterance and generating a coherent response. We investigate how the actual recognition results of 10 different speech recognizers and models result in response appropriateness for a virtual human (Sergeant Blackwell), who was part of a museum exhibit, fielding questions ”in the wild” from museum visitors. Results show a general correlation between WER and response quality, but this pattern doesn’t hold for all recognizers.more » « less
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